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Thomas Neidhart updated MATH-749: --------------------------------- Description: It would be nice to have convex hull implementations for 2D/3D space. There are several known algorithms [http://en.wikipedia.org/wiki/Convex_hull_algorithms]: * Graham scan: O(n log n) * Incremental: O(n log n) * Divide and Conquer: O(n log n) * Kirkpatrick-Seidel: O(n log h) * Chan: O(n log h) The preference would be on an algorithm that is easily extensible for higher dimensions, so *Incremental* and *Divide and Conquer* would be prefered. was: It would be nice to have convex hull implementations for 2D/3D space. There are several known algorithms [http://en.wikipedia.org/wiki/Convex_hull_algorithms]: * Graham scan: O(n log n) * Incremental: O(n log n) * Kirkpatrick-Seidel: O(n log h) * Chan: O(n log h) The preference would be on an algorithm that is easily extensible for higher dimensions, TBD. > Convex Hull algorithm > --------------------- > > Key: MATH-749 > URL: https://issues.apache.org/jira/browse/MATH-749 > Project: Commons Math > Issue Type: New Feature > Reporter: Thomas Neidhart > Priority: Minor > Labels: 2d, geometric > Fix For: 3.1 > > > It would be nice to have convex hull implementations for 2D/3D space. There > are several known algorithms > [http://en.wikipedia.org/wiki/Convex_hull_algorithms]: > * Graham scan: O(n log n) > * Incremental: O(n log n) > * Divide and Conquer: O(n log n) > * Kirkpatrick-Seidel: O(n log h) > * Chan: O(n log h) > The preference would be on an algorithm that is easily extensible for higher > dimensions, so *Incremental* and *Divide and Conquer* would be prefered. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators: https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa For more information on JIRA, see: http://www.atlassian.com/software/jira